Data Scientist vacancy at AlphaSights

At AlphaSights, we search through hundreds of millions of professionals working in the world today to find the small handful of experts qualified to answer our clients' needs. They use these insights to drive amazing progress within their organizations. Our mission is to provide access to dispersed, hidden, and underutilized knowledge.

General overview of the role

AlphaSights' Data Scientists help to build new products and improve search and discovery. Working collaboratively with teams across the company, both within Engineering and with stakeholders, you will apply Machine Learning, data analysis, and predictive analytics to help distinguish signal from noise. You will work with unique, proprietary data sets that offer a window onto the world economy. Ultimately, your work will power the next generation of features to help us build our knowledge on demand offering.

Responsibilities

Have a good degree of autonomy, owning the full spectrum of data driven projects
Build recommendation systems and predictive models
Work directly with stakeholders and teams generating custom data sets to fully understand the problem being modeled
Write production level code to expose the models that you build
Contribute to our open source projects

Requirements

Have 3+ years of industry experience
Have experience with Machine Learning (ML), Statistical Modeling, Recommendation Systems, or Natural Language Processing (NLP)
Have strong SQL skills and enjoy extracting and manipulating data

Other information

You would join a dynamic, multinational, and diverse team who enjoy solving interesting problems in a collaborative environment

Your co-workers will include motivated recent graduates from top Computer Science schools as well as experienced industry leaders from companies such as Google and Amazon

Don't worry if your experience or background doesn't match all of these areas, we believe a broad spectrum of experience provides great perspective on solving problems in new and innovative ways and we’d love to [hear from you].